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Jetson Orin NX SUPER📖
01.Get started
  • 01. Learning route
  • 02. Get started quickly
  • 03. System Update Notes
  • 04.Disabling automatic updates and troubleshooting issues
02.Jetson basic course
  • 01.Jetson board introduction
  • 02.Write Jetson original system
  • 03.Installing Jetson environment
  • 04.Backup SSD system
  • 05.Restore initial image system
  • 06.Upgrade to SUPER version
  • 07.Write SUPER boot
  • 08.SSD expansion
  • 09.Jetpack old system upgraded to Yahboom SUPER factory system
  • 10.Write the system onto your own solid-state drive
03.Basic setting course
  • 01.Basic knowledge
  • 02.Network configuration
  • 03.SSH remote login
  • 04.VNC remote control
  • 05.Remote file transfer
  • 06.Jtop tool
  • 07.Exchange space expansion
  • 08.Use VSCode
  • 09.Use VMware
04.GPIO control course
  • 01.GPIO description
  • 02.GPIO library installation
  • 03.GPIO reading
  • 04.GPIO output
  • 05.Serial communication
  • 06.I2C communication
05.Vision basic course
  • 01.CSI camera preview
  • 02.USB camera preview
  • 03.Use Jupyter Lab
  • 04.Use JetCam
06.OpenCV basic course
  • 01.Image reading
  • 02.Image saving
  • 03.Image modification
  • 04.Image scaling
  • 05.Image cropping
  • 06.Image translation
  • 07.Image mirroring
  • 08.Image grayscale conversion
  • 09.Image binarization
  • 10.Image edge detection
  • 11.Add line segments
  • 12.Add rectangles
  • 13.Add circular shape
  • 14.Add ellipses
  • 15.Add polygons
  • 16.Add Text
  • 17.Preview USB camera image
  • 18.Preview CSI camera image
07.Vision advanced course
01.Environment construction
  • 01.TensorFlow
  • 02.PyTorch
  • 03.Torchvision
02.DeepStream development
  • 01.DeepStream environment
  • 02.Four types of detection(traffic)
03.YOLO11 development
  • 01.YOLO environment construction
  • 02.CLI use
  • 03.Object detection
  • 04.Instance segmentation
  • 05.Pose estimation
  • 06.Image classification
  • 07.Oriented object detection
  • 08.Model conversion
  • 09.Dataset annotation
  • 10.Model training conversion
  • 11.Model prediction
04.Mediapipe development
  • 01.Mediapipe environment
  • 02.Hand detection
  • 03.Face detection
  • 04.Face effects
  • 05.3D object recognition
  • 06.Virtual brush
  • 07.Gesture recognition
  • 08.Finger control
  • 09.Posture estimation
  • 10.Face mask
  • 11.Overall detection
  • 12.Green scene removal(Human)
05.QR code recognition
  • 01.QR code recognition
06.YOLO26 development
  • 01.YOLO environment constructionnew
  • 02.CLI usenew
  • 03.Object detectionnew
  • 04.Instance segmentationnew
  • 05.Pose estimationnew
  • 06.Image classificationnew
  • 07.Oriented object detectionnew
  • 08.Model conversionnew
  • 09.Dataset annotationnew
  • 10.Model training conversionnew
  • 11.Model predictionnew
08.Docker basic course
  • 01.Docker introduction
  • 02.Docker installation
  • 03.Docker command
  • 04.Docker usage
  • 05.Docker interaction
09.ROS1-Melodic
01.ROS1 basic course
  • 01. Introduction to ROS
  • 02. Project file structure
  • 03. Common commands and tools
  • 04. Publisher
  • 05. Subscribers
  • 06. Customize topic messages and use
  • 07. Client
  • 08. Server
  • 09. Customize service messages and usage
  • 10. TF release and monitoring
02.ROS1 vision course
  • 00.Must read before running
  • 01.Camera preview
  • 02.QR code
  • 03.Human posture estimation
  • 04.Target detection
  • 05.AR vision
  • 06.Opencv application
  • 07.ROS+Opencv basics
  • 08.Mediapipe development
10.ROS2-Humble
01.ROS2 basic course
  • 01.Introduction to ROS2
  • 02.ROS2 install Humble
  • 03.ROS2 development environment
  • 04.ROS2 workspace
  • 05.ROS2 function package
  • 06.ROS2 node
  • 07.ROS2 topic communication
  • 08.ROS2 service communication
  • 09.ROS2 action communication
  • 10.ROS2 custom interface message
  • 11.ROS2 parameter service case
  • 12.ROS2 meta-function package
  • 13.ROS2 distributed communication
  • 14.ROS2 DDS
  • 15.ROS2 time related API
  • 16.ROS2 common command tools
  • 17.ROS2 rviz2 use
  • 18.ROS2 rqt toolbox
  • 19.ROS2 Launch startup file configuration
  • 20.ROS2 recording and playback tool
  • 21.ROS2 URDF model
  • 22.ROS2 Gazebo simulation platform
  • 23.ROS2 TF2 coordinate transformation
02.ROS2 vision course
  • 01.Camera preview (USB)
  • 02.Camera preview (CSI)
  • 03.Camera calibration (USB)
  • 04.Camera calibration (CSI)
  • 05.AR vision (USB)
  • 06.AR vision (CSI)
11.Offline AI model coursenew
Offline large model (Text Interaction)
  • 1.AI large model environment deployment
  • 2.Install large model dialogue platform
  • 3.Meta Al Llama3.2 model
  • 4.Alibaba Cloud Qwen3 model
  • 5.Microsoft Phi-4-mini model
  • 6.DeepSeek DeepSeek-R1 model
  • 7.Alibaba Cloud Qwen2.5v visual multimodal large model
  • 8.Google Gemma3 visual multimodal large model
  • 9.Lava visual multimodal large model
  • 10.MiniCPM-V visual multimodal large model
  • 11.Multimodal visual understand application
  • 12.Multimodal text image application
  • 13.Multimodal video analysis application
  • 14.Multi module visual position application
  • 15.Multimodal table scanning application
  • 16.Multimodal autonomous agent application
Offline large model (Voice Interaction)
  • 0.Voice interaction hardware connection (ReadMe)
  • 1.Offline speech to text (ASR)
  • 2.Offline text to speech (TTS)
  • 3.AI large model voice interaction
  • 4.Multimodal visual understand speech interaction
  • 5.Multimodal text and graphics application
  • 6.Multimodal video analysis application
  • 7.Multi module visual position application
  • 8.Multimodal table scanning application
  • 9.Multimodal autonomous proxy application
  • 10.AI large model offline voice assistant
12.Online AI model coursenew
Online large model (Text Interaction)
  • 1.OpenRouter large model API aggregation platform
  • 2.Multimodal visual understand application
  • 3.Multimodal visual localization application
  • 4.Multimodal table scanning application
  • 5.Multimodal autonomous proxy application
Online large model (Voice Interaction)
  • 0.Voice interaction hardware connection (ReadMe)
  • 1.Online speech to text (ASR)
  • 2.Online text to speech (TTS)
  • 3.AI large model voice interaction
  • 4.Multimodal visual understand speech interaction
  • 5.Multi module visual position application
  • 6.Multimodal table scanning application
  • 7.Multimodal autonomous proxy application
  • 8.AI large model online voice assistant
13.NVIDIA lsaac ROS coursenew
  • 1.Build lsaac ROS environment
  • 2.Deep segmentation
  • 3.DNN stereoscopic depth
  • 4.Free space segmentation
  • 5.Image distortion processing
  • 6.Image segmentation
  • 7.3D scene reconstruction and mapping
  • 8.Object detection
  • 9.3D attitude estimation
  • 10.Visual SLAM
14.OpenClaw Deployment and Basic Usagenew
  • 01.OpenClaw Quick Start on Jetson Platform
  • 02.OpenClaw Deployment
  • 03.OpenClaw WhatsApp Plugin Application
  • 04.OpenClaw WebChat Interaction
  • 05.OpenClaw TUI Interaction
  • 06.OpenClaw Tools Introduction
  • 07.OpenClawGate Gateway User Manual
  • 08.OpenClaw Features Overview
  • 09.OpenClawHub Introduction (Skill Installation)
  • 10.OpenClaw Application - File Management
  • 11.OpenClaw Application - Camera
  • 12.OpenClaw Application - Browser Control
  • 13.OpenClaw Application - Script Execution
  • 14.OpenClaw Application - AI Programming (Peripheral & GPIO Control)
  • 15.OpenClaw Application - Dedicated AI Assistant
  • 16.OpenClaw Web Search Capability Configuration
15.OpenClaw Advanced Developmentnew
1.Preparation Before Use
  • 1. Peripheral Hardware Configuration
  • 2. OpenClaw API Key Configuration
  • 3. OpenClaw Model Switching
  • 4. OpenClaw Prompts
  • 5. AI Voice Interaction Configuration
  • 6. Three Dialogue Configuration Tests
2.OpenClaw AI Programming Peripheral Control
  • 1. Servo Control
  • 2. RGB Strip
  • 3. OLED Display
  • 4. Temperature and Humidity Sensor
  • 5. Camera Application
  • 6. AI Script Peripheral Control
3.OpenClaw Peripheral Integration Applications
  • 1. Plant Care Assistant
  • 2. AI Calorie Estimation
  • 3. AI Rock Paper Scissors Game
  • 4. AI Pet
  • 5. AI Weather Station
  • 6. Temperature and Humidity Dashboard
  • 7. Scheduled Tasks
Download
  • System_File
  • VM_File
  • 3D_Model_File
  • Data_Sheet_File
  • Software_Tools
  • Code
  • Instruction_Manual
  • ROS2_Basic_VM
Download ZIP

Welcome to Jetson Orin NX SUPER repository

当製品の日本語版マニュアル資料は、こちらからご取得ください。

05.OpenClaw TUI Interaction

5. OpenClaw TUI Interaction

The TUI (Text User Interface) serves as OpenClaw's "command-line chat window." When it is inconvenient to access the web console on your Jetson device—or if you are connected remotely via SSH—the TUI allows you to perform most daily interactions directly within your terminal: engaging in dialogue, switching models, checking status, managing sessions, invoking skills, and more.

OpenClaw TUI Interface (Replace with your own screenshot)

1. How to Access the TUI

Execute the following command in your terminal:

openclaw tui

If you have already launched the OpenClaw gateway (e.g., the gateway/server component) in a separate terminal session, you can simply run openclaw tui to enter the interactive interface.

For non-Docker versions, the OpenClaw gateway does not require manual startup; it launches automatically upon system boot.

For Docker versions (such as on the Jetson Nano), you must first open a terminal and manually run openclaw gateway to start the gateway service.

2. What is the TUI Interface?

You can think of the TUI as a "chat box with built-in commands":

  • Upper Section: Dialogue History (messages you sent, model responses, and tool/skill outputs).
  • Lower Section: Input Field (where you type questions or send slash commands).
  • Sending Messages: Press Enter after typing to send your input.

When accessing the TUI for the first time, it is recommended that you perform two initial actions:

xxxxxxxxxx
/status

3. Slash Commands

Slash commands typically need to be sent as standalone messages beginning with a forward slash (/); they are used to control the current session and execute specific operations.

CommandFunctionWhen to UseExample
/helpView help and command listWhen you don't know what commands are available/help
/statusCheck current statusIf you suspect a connection issue or want to check context usage/status
/newStart a new conversation thread (New Session)To switch topics or avoid context interference/new
/resetReset the session (Equivalent to starting over; has the same effect as /new)If the conversation has gone off track or you want to clear the context/reset
/model / /models listView/Switch modelsWhen you want to switch to a faster or more powerful model/models list
/think mediumSet the "thinking depth"For daily use, low or off is recommended/think medium
/stopAbort the current taskIf the system gets stuck or you want to stop immediately/stop
/context detailView the currently injected contextTo troubleshoot "why it remembers/forgets certain details"/context detail
/compactCompress older history into a summaryWhen the conversation is too long or the context buffer is nearly full/compact
/skill <name>Run a specific skillWhen you know the skill name and want to execute it directly/skill web_search

Two additional tips for a smoother "daily workflow":

  • It is safest to include only one slash command per message.
  • To quickly browse through all available commands, use /help or /commands.

4. Sessions and Memory

In OpenClaw, the roles of these two concepts are clearly defined:

  • Session: Manages "where the current conversation stands." When you use /new or /reset within the TUI, you are essentially switching to—or restarting—a session.
  • Memory: Manages "content that should be retained long-term, even across different sessions." This data is written to disk (in Markdown format) and can be retrieved back into the current session whenever needed. ### 4.1 Where Are Session Files Located?

Sessions are persisted to disk in JSONL format. Common locations include (subject to your actual installation path):

  • Index: ~/.openclaw/agents/<agentId>/sessions/sessions.json
  • Transcripts: ~/.openclaw/agents/<agentId>/sessions/<SessionId>.jsonl

For troubleshooting purposes, a more convenient approach is to first execute:

xxxxxxxxxx
openclaw status

This command typically displays the storage path as well as information regarding recent sessions.

4.2 How to "Put Memory to Use"

You can think of Memory as "having the bot take notes":

  • memory/YYYY-MM-DD.md: A daily process log, suitable for recording progress and ad-hoc decisions.
  • MEMORY.md: Long-term, stable information (preferences, fixed rules, project constraints, etc.).

Practical Tips:

  • To make a specific conclusion accessible across multiple sessions: Simply tell the bot, "Write this into MEMORY.md."
  • When preparing to switch to a new topic using /new: First use /compact—or write key decisions into Memory—before switching sessions.

5. Quick Start Workflow

  1. Enter the TUI: openclaw tui
  2. Check Status: /status
  3. Select a Model: /models list → /model <Number or Name>
  4. Daily Conversation: Simply type your question and press Enter.
  5. Switch Topics: /new
  6. Context Too Long: /compact
  7. Preserve Key Conclusions Long-Term: Ask the bot to write them into Memory.

6. Troubleshooting Common Issues

6.1 Commands Are Unresponsive

  • Ensure the command is sent on a separate line (do not mix it with regular text).
  • Use /help first to check which commands are supported in your current version.

6.2 The Bot Starts "Rambling" or "Misunderstanding You," or Seems Distracted by History

  • Start a new session: /new or /reset
  • Check what context is currently being injected: /context detail

6.3 Responses Are Becoming Increasingly Slow

  • Reduce "thinking depth": /think low or /think minimal
  • Compress conversation history: /compact
OpenClaw WebChat Interaction
OpenClaw Tools Introduction

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